Haydar Ozkan

Cellphone-Based Hand-Held Microplate Reader for Point-of-Care Testing of Enzyme-Linked Immunosorbent Assays

Standard microplate based enzyme-linked immunosorbent assays (ELISA) are widely utilized for various nanomedicine, molecular sensing, and disease screening applications, and this multiwell plate batched analysis dramatically reduces diagnosis costs per patient compared to nonbatched or nonstandard tests. However, their use in resource-limited and field-settings is inhibited by the necessity for relatively large and expensive readout instruments. To mitigate this problem, we created a hand-held and cost-effective cellphone-based colorimetric microplate reader, which uses a 3D-printed opto-mechanical attachment to hold and illuminate a 96-well plate using a light-emitting-diode (LED) array. This LED light is transmitted through each well, and is then collected via 96 individual optical fibers. Captured images of this fiber-bundle are transmitted to our servers through a custom-designed app for processing using a machine learning algorithm, yielding diagnostic results, which are delivered to the user within ∼1 min per 96-well plate, and are visualized using the same app. We successfully tested this mobile platform in a clinical microbiology laboratory using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests using a total of 567 and 571 patient samples for training and blind testing, respectively, and achieved an accuracy of 99.6%, 98.6%, 99.4%, and 99.4% for mumps, measles, HSV-1, and HSV-2 tests, respectively. This cost-effective and hand-held platform could assist health-care professionals to perform high-throughput disease screening or tracking of vaccination campaigns at the point-of-care, even in resource-poor and field-settings. Also, its intrinsic wireless connectivity can serve epidemiological studies, generating spatiotemporal maps of disease prevalence and immunity.

Imaging and Sizing of Single DNA Molecules on a Mobile Phone

DNA imaging techniques using optical microscopy have found numerous applications in biology, chemistry and physics and are based on relatively expensive, bulky and complicated set-ups that limit their use to advanced laboratory settings. Here we demonstrate imaging and length quantification of single molecule DNA strands using a compact, lightweight and cost-effective fluorescence microscope installed on a mobile phone. In addition to an optomechanical attachment that creates a high contrast dark-field imaging setup using an external lens, thin-film interference filters, a miniature dovetail stage and a laser-diode for oblique-angle excitation, we also created a computational framework and a mobile phone application connected to a server back-end for measurement of the lengths of individual DNA molecules that are labeled and stretched using disposable chips. Using this mobile phone platform, we imaged single DNA molecules of various lengths to demonstrate a sizing accuracy of <1 kilobase-pairs (kbp) for 10 kbp and longer DNA samples imaged over a field-of-view of ∼2 mm2.

Yeast viability and concentration analysis using lens-free computational microscopy and machine learning

Research laboratories and the industry rely on yeast viability and concentration measurements to adjust fermentation parameters such as pH, temperature, and pressure. Beer-brewing processes as well as biofuel production can especially utilize a cost-effective and portable way of obtaining data on cell viability and concentration. However, current methods of analysis are relatively costly and tedious. Here, we demonstrate a rapid, portable, and cost-effective platform for imaging and measuring viability and concentration of yeast cells. Our platform features a lens-free microscope that weighs 70 g and has dimensions of 12 × 4 × 4 cm. A partially-coherent illumination source (a light-emitting-diode), a band-pass optical filter, and a multimode optical fiber are used to illuminate the sample. The yeast sample is directly placed on a complementary metal-oxide semiconductor (CMOS) image sensor chip, which captures an in-line hologram of the sample over a large field-of-view of >20 mm2. The hologram is transferred to a touch-screen interface, where a trained Support Vector Machine model classifies yeast cells stained with methylene blue as live or dead and measures cell viability as well as concentration. We tested the accuracy of our platform against manual counting of live and dead cells using fluorescent exclusion staining and a bench-top fluorescence microscope. Our regression analysis showed no significant difference between the two methods within a concentration range of 1.4 × 105 to 1.4 × 106 cells/mL. This compact and cost-effective yeast analysis platform will enable automatic quantification of yeast viability and concentration in field settings and resource-limited environments.

Single DNA imaging and length quantification through a mobile phone microscope

The development of sensitive optical microscopy methods for the detection of single DNA molecules has become an active research area which cultivates various promising applications including point-of-care (POC) genetic testing and diagnostics. Direct visualization of individual DNA molecules usually relies on sophisticated optical microscopes that are mostly available in well-equipped laboratories. For POC DNA testing/detection, there is an increasing need for the development of new single DNA imaging and sensing methods that are field-portable, cost-effective, and accessible for diagnostic applications in resource-limited or field-settings. For this aim, we developed a mobile-phone integrated fluorescence microscopy platform that allows imaging and sizing of single DNA molecules that are stretched on a chip. This handheld device contains an opto-mechanical attachment integrated onto a smartphone camera module, which creates a high signal-to-noise ratio dark-field imaging condition by using an oblique illumination/excitation configuration. Using this device, we demonstrated imaging of individual linearly stretched λ DNA molecules (48 kilobase-pair, kbp) over 2 mm2 field-of-view. We further developed a robust computational algorithm and a smartphone app that allowed the users to quickly quantify the length of each DNA fragment imaged using this mobile interface. The cellphone based device was tested by five different DNA samples (5, 10, 20, 40, and 48 kbp), and a sizing accuracy of <1 kbp was demonstrated for DNA strands longer than 10 kbp. This mobile DNA imaging and sizing platform can be very useful for various diagnostic applications including the detection of disease-specific genes and quantification of copy-number-variations at POC settings.

Cellphone-based hand-held microplate reader for point-of-care ELISA testing(Conference Presentation)

Enzyme-linked immunosorbent assay (ELISA) in a microplate format has been a gold standard first-line clinical test for diagnosis of various diseases including infectious diseases. However, this technology requires a relatively large and expensive multi-well scanning spectrophotometer to read and quantify the signal from each well, hindering its implementation in resource-limited-settings. Here, we demonstrate a cost-effective and handheld smartphone-based colorimetric microplate reader for rapid digitization and quantification of immunoserology-related ELISA tests in a conventional 96-well plate format at the point of care (POC). This device consists of a bundle of 96 optical fibers to collect the transmitted light from each well of the microplate and direct all the transmission signals from the wells onto the camera of the mobile-phone. Captured images are then transmitted to a remote server through a custom-designed app, and both quantitative and qualitative diagnostic results are returned back to the user within ~1 minute per 96-well plate by using a machine learning algorithm. We tested this mobile-phone based micro-plate reader in a clinical microbiology lab using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests on 1138 remnant patient samples (roughly 50% training and 50% testing), and achieved an overall accuracy of ~99% or higher for each ELISA test. This handheld and cost-effective platform could be immediately useful for large-scale vaccination monitoring in low-infrastructure settings, and also for other high-throughput disease screening applications at POC.

Comparative analysis of poly(N-methylpyrrole) and its titanium dioxide nanocomposite film formations against equivalent electrical circuit model for the their corrosion-inhibition effects

Conducting polymers have been used for many years as coating materials against corrosion. However, the coated materials absorb water over time resulting in reduction of resistivity and anticorrosion properties. In this study, poly(N-methylpyrrole) (P(N-MPy)) and P(N-MPy)/titanium dioxide ((TiO2) nanocomposite films were synthesized in 0.5 M oxalic acid solution on Al 1050 electrode by chronoamperometric method. The modified electrodes were characterized by scanning electron microscopy–energy dispersive X-ray analysis, Fourier transform infrared–attenuated transmission reflectance, electrochemical impedance spectroscopy (EIS), and Tafel extrapolation techniques. The corrosion tests results were obtained in 3.5% sodium chloride (NaCl) solution by Tafel plots. In addition, the equivalent electrical circuit model of P(N-MPy) and P(N-MPy)/TiO2 nanocomposite films were investigated in 3.5% NaCl solution at different time periods. The EIS study of the polymer and nanocomposite were analyzed by Matlab program and for the first time Tina, the equivalent electrical circuits program, was used.